High speed communication systems capable of higher throughput data rates are emerging. Gigabit Ethernet networks may communicate information at 1 gigabits-per-second (Gbps) or higher over high speed channels. Different Ethernet protocols exist such as those as defined by the Institute of Electrical and Electronics Engineers (IEEE) 802.3 series of standards. For example, a recent protocol is the IEEE Proposed Standard 802.3an titled “IEEE Standard For Information Technology—Telecommunications and information exchange between systems—Local and metropolitan networks—Specific requirements Part 3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) Access Method and Physical Layer Specifications: Amendment: Physical Layer and Management Parameters for 10 Gb/s Type 10GBASE-T,” Draft Amendment P802.3an/Draft 3.1, 2005 (“10GBASE-T Specification”). In addition to Ethernet communication, other communication systems that operate in full duplex mode include digital subscriber lines (DSL) such as asynchronous DSL (ADSL).
These high speed channels typically implement a training or adaptation when beginning operation to enable a receiver to lock to a transmitter. When the receiver begins operation, a sampling phase and frequency is typically adjusted in order to sample the received signal at a phase which provides a suitable eye opening (or small mean square error (MSE) between detected signal and determined symbol). This adjustment, e.g., timing recovery (TR) is done using a control loop that attempts to minimize a measurement of the phase error. The eye opening/MSE can only be measured at the symbol slicer's input after a linear feed-forward equalizer (FFE), so the optimal phase depends on the FFE. Current phase error estimators typically require correct decisions of the symbol slicer.
However, the received signal may require some equalization in order to have an eye opening at all, otherwise the symbol slicer might make wrong decisions. The equalizer starts from an initial estimate using partial information on the transmission channel, and uses an adaptation algorithm (e.g., a least mean square (LMS)) to modify its coefficients in order to minimize the noise power at its output. However, estimating the noise power requires that the symbol slicer make correct decisions, which in turn requires stable phase and frequency locking. Thus a circular dependence exists, and current solutions typically require a long time to perform the adaptation.